Author

Alyssa Farrell leads global industry marketing for SAS’ business within the energy sector, including Utilities, Oil and Gas. In this role, she focuses on the SAS solutions that help optimize our energy infrastructure by applying predictive analytics to complex data. She currently serves on the Advisory Committee of the Research Triangle Cleantech Council and co-leads the Program and Communications Action Committee, as well as a Working Group of the Utility Analytics Institute. She is a member of the Society of Petroleum Engineers (SPE). Farrell regularly speaks with trade associations, analysts, and the press about the opportunities organizations have to effectively manage a sustainable energy analytics strategy and drive healthy economic growth.
Prior to joining SAS, Farrell was a senior consultant in the Deloitte Public Sector practice. In this capacity, she was a project manager for state-wide and county-wide systems implementations and was responsible for user acceptance testing, change management and training, and middleware technology selection.
She is a graduate of the Eller College of Management at the University of Arizona, where she earned her MBA degree with a concentration in Management Information Systems. She also holds a Bachelor of Arts degree from Duke University.

Widespread flooding. Downed power lines. Broken poles. Failed transformers and breakers. Leaking pipes. Shut down refineries. The toll that a catastrophic storm takes on the energy value chain is significant. A functioning power grid, clean water and reliable fuel sources are critical for public safety and economic recovery. Even with

Utilities can save as much as $10 million a year for every one percent improvement in forecast accuracy by optimizing asset utilization and trading strategies. Changing energy markets and an influx of data from the smart grid are providing more opportunities to reap value from energy forecasting. Improving energy forecasts

Tell me if you’ve heard this before: Your company hired (or re-titled) a talented data scientist and they have great skills and no data. Or they're marginalized by IT because they're misunderstood. They're offered “cleansed” data that will fit into the hardware provisioned. What they want is “all” relevant data

The utility industry is ripe with analytic opportunities. Usually, when I share that perspective, thoughts immediately jump to making the energy grid more efficient. Certainly, there are efficiencies to gain with improved data about where power is being consumed and the sources that are available to support it. However, there

Energy suppliers are fighting for prime position in the domestic energy supply market. Disillusioned customers, increased competition due to a flood of new entrants and tighter regulations are forcing suppliers to reassess their business models. According to UK regulator Ofgem, there were 3.8 million account switches in the first six

Research indicates that IoT and Machine Learning are more valuable to utilities when used in combination but there are hurdles to overcome first. Machine learning and IoT will enable utilities to better realize the next generation of the power grid: a distributed system with power flows among millions of things

The Internet of Things (IoT), sensors and connected devices are all the buzz leading up to DistribuTECH (Feb 9-11), so I sat down with one of our IoT specialists, Lorry Hardt to learn more. Lorry will be at DistribuTECH to support our joint demonstration with Intel and gave me the

Operations technology (OT), such as control systems, are crucial elements in our daily lives. They make the stoplights function at intersections. They guide robots with precise movements on the shop floor. Their switches and routers are the backbone of our internet. But what if they were even more intelligent? What

Whether it’s a smart water meter or a complex combustion turbine, expectations of reliability for complex, connected machines have increased across the board. Due to higher visibility and the availability of advanced analytics, companies know they should be able to identify emerging safety and reliability issues in these assets. By

As utilities expand analytic capabilities into more areas of the business, the reality of the data management challenge becomes very real. Most have accepted the era of "big data." But what about the quality of that big data? Is it reliable? What about the governance? Have the processes changed since

Whether it’s to reduce churn in competitive markets or to elevate customer satisfaction rankings in regulated markets, customer analytics is hot right now in utilities. However, the complexity that utilities have built into their processes and technologies over the past decades makes customer analytics a more challenging issue to tackle

Oil companies are being forced to explore in geologically complex and remote areas to exploit more unconventional hydrocarbon deposits. New engineering technology has pushed the envelope of previous upstream experience. No guidebook existed on how computing methodologies can contribute to E&P performance at reduced risk. Until now. A new book

I was asked to speak recently on a topic that includes two hyped terms: Big data and sustainability. At the risk of igniting an anti-buzzword campaign, I added a third over-used term to that list: analytics. Even though individuals and companies use those three words – big data, sustainability, and

"Big data" is a big deal for electric utilities. In a smart power grid, when you turn on the lights, you're generating data. When your neighbor plugs in his electric vehicle, he's generating data. When a heat wave causes retailers to crank up the air conditioning, they're generating data. All

How often do you question the availability of power? Outside of weather events, the answer is probably, “not much.” But what if you have an electric vehicle? Or manage a data center? Rely on either of those technologies and you might consider electricity as a constraint, around which you plan

Contrary to popular belief, utility executives are ramping up for “big data” in a “big way.” This industry, which historically focused on operational technologies like pole-mounted hardware, is making a big shift to information technologies to support initiatives such as distribution optimization and fraud detection. We recently invited senior utility

Managing the deluge of smart grid data. Responding to the increased demand for customer intelligence. Implementing analytics for grid optimization. These were just a few of the topics covered at this week’s inaugural “Utility Analytics Summit.” Utilities have been grappling with implementation of smart grid devices for several years and

I just returned from the largest annual gathering of upstream oil and gas technology professionals. Some of the brightest minds in resource exploration – from graduate students to 50-year professionals – enjoyed the masquerade carnival that filled the exhibit hall on Halloween night. But the real entertainment was in the sessions.